Wakeword Project Phase 2 Deliverables

[secretsauceai]

Phase two of the Wakeword Project

Each step usually consists of training several (at least 5) models (using the same and other collected data to remove bias) and evaluating their results to ensure that the models aren't randomly performing well.

• Models (first tf1.13, then tflite) must pass minimum quality control: 5 wake up in a row, 2h random input (ie 1h TV and 1h conversation) without false wake up
  • tf 1.13
  • tflite (this test is on hold for improvements to the incremental training methods)
• Models must pass production quality control: 1 week: wake up every time, ~2-3 false wake ups (future goal: 1 false wake up per week!)
  • tflite
    • this is the current blocker for production level tflite models
• Use Wake Word Data Prep models to test TF lite compression optimization
  • Once tflite has passed both quality controls, it's time to compress further!
  • Benchmark performance (CPU% raspi4, loss of quality of model)
• Precise Rust
  • Runner
  • MFCC in rust

Precise tflite

• Create new branch of Precise reflecting the results on compression (include CLI for people to pick between levels of compression)